An adaptive multi-agent based architecture for engineering education

Jara-Roa, Dunia Ines; Valdiviezo-Díaz, Priscila; Agila-Palacios, Martha Vanessa; Sarango-Lapo, Celia Paola; Rodriguez-Artacho, Miguel

doi:10.1109/educon.2010.5492574

Cited by 3 publications

(2 citation statements)

References 5 publications

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“…These systems have the ability to communicate with each other to make decisions and thus perform a task in a simpler way. Multi-Agent systems are currently used in different applications, ranging from e-commerce [41][42][43] to education [44][45][46].…”

Section: Agent Systemmentioning

confidence: 99%

Autonomous Population Regulation Using a Multi-Agent System in a Prey–Predator Model That Integrates Cellular Automata and the African Buffalo Optimization Metaheuristic

2019

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This research focused on the resolution of a dynamic prey–predator spatial model. This model has six life cycles and simulates a theoretical population of prey and predators. Cellular automata represent a set of prey and predators. The cellular automata move in a discrete space in a 2d lattice that has the shape of a torus. African buffaloes represent the predators, and the grasslands represent the prey in the African savanna. Each buffalo moves in the discrete space using the proper motion equation of the African buffalo optimization metaheuristic. Two types of approaches were made with five experiments each. The first approach was the development of a dynamic prey–predator spatial model using the movement of the African buffalo optimization metaheuristic. The second approach added the characteristic of regulating the population of buffaloes using autonomous multi-agents that interact with the model dynamic prey–predator spatial model. According to the obtained results, it was possible to adjust and maintain a balance of prey and predators during a determined period using multi-agents, therefore preventing predators from destroying an entire population of prey in the coexistence space.

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Section: Agent Systemmentioning

confidence: 99%

Autonomous Population Regulation Using a Multi-Agent System in a Prey–Predator Model That Integrates Cellular Automata and the African Buffalo Optimization Metaheuristic

2019

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“…For example, an intelligent agent for making instructional decisions allows visualization of the adaptive effect generated by the interaction of the components [13].…”

Section: Intelligent Agentsmentioning

confidence: 99%

Enhanced Education by Using Intelligent Agents in Multi-Agent Adaptive e-Learning Systems

Alexandru¹,

Tîrziu²,

Tudora³

et al. 2015

SIC

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The evolution of Web technologies has made e-Learning a popular common way to teach and learn both in school and non-school settings. This paper provides an education-oriented approach for building personalized e-Learning environments that focuses on putting the learners' needs in the centre of the development process. The proposed agentbased adaptive architecture extends Moodle platform in order to support instructional decisions and adaptive behaviour. The paper describes the characteristics, functions, and interactions of the agents which take part in each module of the adaptive architecture, as well as an intelligent agent for instructional decisions making. The aim of this agent is to collect information generated by the rest of agents and to provide the best personalised support for the final users, tutors and students, taking into account their attitudes towards the learning environment.

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